10 customer experience implementations of AI


10 customer experience implementations of artificial intelligence


The possible implementations of artificial intelligence are virtually unlimited, and customer experience is an area where AI can be effectively applied. AI helps us to understand customer journeys, pain points, and intentions in ways that a human or a rule-based programme wouldn’t be able to. Adopting AI allows companies to better deal with customer queries and improve the overall experience, by providing real-time solutions or predicting future actions. In fact, research company Gartner predicts that “By 2020, customers will manage 85% of their relationship with the enterprise without interacting with a human”. Read on for 10 customer experience implementations of artificial intelligence.

1. AI chatbots for ordering products

AI chatbots are being used to make it even easier for customers to order products online, especially items such as take-away food or flowers to be delivered. Chatbots are able to make recommendations based on previous purchases, browsing habits, and conversational cues. These recommendations can include the topping to add to a pizza or the type of flowers that will best suit an occasion. For example, Domino’s Pizza allows customers to order a pizza using a chatbot. Users start by typing ‘pizza’, and then the chatbot takes them through each stage of ordering, including payment and delivery tracking. With smart suggestions and a simple, familiar interface, these chatbots streamline the ordering process for a more efficient online experience.

2. Personal shopping assistants

AI assistants are being used to improve a customer’s online shopping experience. They act like personal assistants and make recommendations based on your preferences and reasons for purchasing. Perhaps the most famous example is North Face using IBM’s Watson AI computer on their website. Instead of having to sort through their extensive product catalogue, Watson will ask questions such as where you’re planning to wear their clothing and what activities you plan to do with it. This information will be used to provide the most relevant clothing options for your particular requirements.

3. Voice assistants on phone calls

Automated voice assistants have been used for a while. They are most commonly encountered on customer service calls to larger companies, whereby the caller would answer questions by pressing numbers on their keypad. These questions are typically designed to direct the caller to the most relevant department for their enquiry. However, with AI, voice assistants are becoming more helpful and tend to bypass human interaction altogether. Additionally, AI voice assistants use natural language processing to more accurately discover the caller’s intent. This means they are able to offer more appropriate recommendations faster, instead of a caller having to listen to endless menu options being read.

4. More accurate delivery information

Using AI, companies can make very accurate predictions about not only their own internal logistics and deliveries but also about what their customers are likely to order. For example, manufacturing company Infinera used AI to analyse their own supply chain, leading to better predictions of future stock levels and delivery times. This predictive application of AI could soon be extended to more areas of commerce, and the improved accuracy of stock and delivery information is hugely beneficial for the customer experience.

5. Personalised content recommendations

This is perhaps the most familiar application of AI mentioned on our list. Entertainment companies like Spotify and Netflix use AI to give users personalised recommendations of content they’ll likely enjoy based on previous television shows or movies they have selected. It may seem relatively simple, but this feature plays a large role in the popularity of these services. They enrich the media experience by offering, effectively, a virtual assistant for music and movies as standard.

6. Fraud prevention

Ticket scalping is where people buy up a large number of tickets as soon as they become available in order to sell them on for a considerable profit. It has been a big problem for event organisers for decades, and even more so in recent years as buying tickets online has become the norm. Fraudsters will use bots to scour ticket-selling websites, such as Ticketmaster, buy lots of tickets instantly, and then post them for sale on third-party websites.

The highest-profile case of ticket scalping in the last few years was for the Mayweather vs Pacquiao boxing match in 2015 - the majority of tickets were swept up by scalpers and were being sold for up to £94,000 each. As a result, Ticketmaster saw the need for innovation and turned to AI. Ticketmaster’s AI system now analyses data on user behaviour, browsing habits, and purchase history to ensure buyers are not only human, but legitimate buyers rather than scalpers. Their efforts have significantly reduced the chances of tickets reaching third-party sites and more customers have been able to buy tickets at reasonable prices.

7. Photo apps tagging pictures

This is another relatively simplistic but very useful application of AI. Photo apps have long been able to tag the date and time that a picture was taken, but with AI, considerably more information can be logged. For example, apps can use facial recognition to instantly name and tag people in photos, and even collate photos taken on holiday into montages using location data. This feature automates a process that used to be very manual and time-consuming.

8. Automatic language translation

The modern world often requires global communication. International language barriers between businesses and customers in different countries can be broken down using AI. AI language detection and translation tools offer more accuracy than traditional translation tools. Artificially intelligent translation tools, especially those that incorporate Machine Learning, have a far greater understanding of context and natural language. They use neural networks, much like the human brain, and make connections between vast amounts of data to recognise and translate entire sentences instead of translating word-by-word. This results in higher-quality translations and a smooth, satisfying customer experience.

9. Order prediction in restaurants

Some restaurants are testing the use of AI facial recognition software that will predict what a customer will order based on their features and behaviour. In China, KFC have partnered with tech giant Baida to develop in this area. The software gauges a person’s age, mood, and gender, and recommends a meal that it believes is suitable. Customers can reject the recommendation and view other options, and the system will save this preference and learn from it. Over time, this technology will become remarkably accurate and will also remember previous orders that customers have made. The aim is to provide a more personal service - it can be thought of as a software version of your local barista remembering your coffee order each morning. This will eventually save customers a lot of time and streamline the entire process of ordering food and drink.

10. AI chatbots for customer service

We’ve touched on chatbots already, but they’re worth mentioning again for customer service specifically. With an artificially intelligent chatbot, customers can receive support 24 hours a day and often have problems resolved faster than by speaking to a human. They also remove the need for potentially long phone calls and waiting times. In our world of on-demand access, customers expect fast and efficient customer service, and that’s what AI chatbots provide.

Artificial intelligence is constantly evolving, and its benefits to customers continue to grow. Our AI chatbots have proven beneficial to a number of businesses, from the AA to GamesRadar+. Browse our resources to find out more about the uses of AI, and take your customer service to the next level.